Autonomous vehicles or self-driving cars are prevalent nowadays, many vehicle manufacturers, and other tech companies trying to develop autonomous vehicles. One major goal of the algorithms is perform manoeuvres safely, even when some anomaly arises. To solve these kinds complex issues, Artificial Intelligence Machine Learning methods used. motion planning problems tires lose their grip on road...

Electrostatic charge of solid particles can cause problems in many handling processes and need to be evaluated terms levels polarity. An inductive sensor is suitable for the evaluation both distributions particle charges at same time. However, performance sensing critically subject its signal process, which result huge errors. One error sources drifting baseline tracked, leads raw signals gener...

1. A longstanding view of simple cells is that they sum their inputs linearly. However, the linear model falls short of a complete account of simple-cell direction selectivity. We have developed a nonlinear model of simple-cell responses (hereafter referred to as the normalization model) to explain a larger body of physiological data. 2. The normalization model consists of an underlying linear ...

Abstract A novel scheme has been developed to show that the observed phase behavior associated with subpulse drifting from two pulsars, J1034−3224 and J1720−2933, can be used obtain magnetic field configuration in partially screened gap (PSG). The outflowing plasma along open line region of pulsars is generated as a result spark discharges an inner acceleration (IAR) above polar cap. IAR modele...

Patchy occurrences of benthic drift algae (i.e. loose lying macroalgal mats) may increase habitat complexity on normally bare soft bottoms, but at the same time, extensive amounts of drifting algal mats are known to stress the benthic fauna. This paper presents results of the first detailed study of the fauna associated with drift algal mats in the northern Baltic Sea. In order to assess the im...